One of the fundamental problem areas in speech and language research, particularly with regards to perception, cognition and artificial intelligence, concerns the characterization of the functional units into which speech sounds are grouped by a receiver (person or machine). A core issue concerns the context-sensitivity of these functional units, or the manner in which the perceptual grouping into functional units can depend upon the spatio-temporal patterning of the entire speech stream. Another core issue concerns the adaptive tuning of recognition mechanisms, and the manner in which such tuning can alter the groupings which emerge within a context of familiar elements. Adaptive tuning of recognition processes is one of the mechanisms whereby representations become unitized or chunked into coherent recognition codes through experience.
For example, a word such as "myself" is used by a person as a unitized verbal chunk. In different contexts, however, the components "my", "self", and "elf" of "myself" are all used as words in their own right. Moreover, although an utterance which ended with the term "my" would generate one grouping of the speech stream, an utterance which went on to include the entire word "Myself" could supplant this one grouping with one appropriate to the longer word. Thus in order to understand how context-sensitive language units are perceived by a receiver, an analysis must be made of how all possible groupings of the speech stream are analyzed through time and how certain groupings are chosen in one context without preventing other groupings from being chosen in a different context.
A similar problem is solved during visual object recognition and figure-ground segmentation, and cognitive information processing. For example, letters such as E contain as parts, letters such as L and F.
Furthermore, the functional units into which an observer groups a speech or visual stream of data are dependent upon the observer's prior language experiences. For example, a unitized representation for the word "myself" does not exist in the brain of an observer who is unfamiliar with this word. Thus an adequate theory of how an observer parses and adaptively groups a speech stream into context sensitive language units needs to analyze how developmental and learning processes bias the observer to experience some perceptual groupings above others. Such developmental and learning process are often called processes of "self-organization" in theoretical biology and physics (Synergetics of the Brain. E. Basar, H. Flohr, H. Haken, and A. Mandell, (Eds.), New York: Sprunger-Verlag, 1983). B. Lindstom, P. MacNeilage, and M. Studdert-Kennedy in 1983 have recently suggested the importance of self-organizing processes in speech perception ("Self-Organizing Processes and the Explanation of Phonological Universals", Explanations of Linguistic Universals. Butterworth, Comrie and Dahl (Eds.) The Hague: Mouton.
Stephen Grossberg introduced the "Adaptive Resonance Theory" in "Adaptive Pattern Classification and Universal Recoding, I: Paralleled Development and Coding of Neural Feature Detectors", Bioligical Sybernetics, 1976. The theory has since undergone extensive development and application. One such development is a theory of speech and language perception which arose from an analysis of how a language system self-organizes in real-time in response to its complex input environment. Stephen Grossberg, "A Theory of Human Memory: Self-Organization and Performance of Sensory-Motor Codes, Maps, and Plans", Progress in theorectical Biology. R. Rosen and F. Snell (Eds.), New York: Academic Press, 1978; and Stephen Grossberg, "Studies of Mind and Brain: Neural Principles of Learning, Perception, Development, Cognition, and Motor Control", Reidel Press, Boston 1982. This approach emphasized the moment-by-moment dynamical interactions that control language development, learning, and memory, and introduced a neural model called a masking field.
The present invention quantitively analyzes and further develops the masking field as the core process within the theory of speech and language perception which solves the adaptive grouping problem in the Adaptive Resonance Theory, and more particularly shows how internal language representations encode a speech stream in a context-sensitive fashion. In addition, a masking field solves a similar grouping problem in applications to visual object recognition and cognitive information processing.